Literature DB >> 26087879

Computational fluid dynamics vs. inverse dynamics methods to determine passive drag in two breaststroke glide positions.

L Costa1, V R Mantha2, A J Silva3, R J Fernandes1, D A Marinho4, J P Vilas-Boas1, L Machado1, A Rouboa5.   

Abstract

Computational fluid dynamics (CFD) plays an important role to quantify, understand and "observe" the water movements around the human body and its effects on drag (D). We aimed to investigate the flow effects around the swimmer and to compare the drag and drag coefficient (CD) values obtained from experiments (using cable velocimetry in a swimming pool) with those of CFD simulations for the two ventral gliding positions assumed during the breaststroke underwater cycle (with shoulders flexed and upper limbs extended above the head-GP1; with shoulders in neutral position and upper limbs extended along the trunk-GP2). Six well-trained breaststroke male swimmers (with reasonable homogeneity of body characteristics) participated in the experimental tests; afterwards a 3D swimmer model was created to fit within the limits of the sample body size profile. The standard k-ε turbulent model was used to simulate the fluid flow around the swimmer model. Velocity ranged from 1.30 to 1.70 m/s for GP1 and 1.10 to 1.50 m/s for GP2. Values found for GP1 and GP2 were lower for CFD than experimental ones. Nevertheless, both CFD and experimental drag/drag coefficient values displayed a tendency to jointly increase/decrease with velocity, except for GP2 CD where CFD and experimental values display opposite tendencies. Results suggest that CFD values obtained by single model approaches should be considered with caution due to small body shape and dimension differences to real swimmers. For better accuracy of CFD studies, realistic individual 3D models of swimmers are required, and specific kinematics respected.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Breaststroke; Computational fluid dynamics (CFD); Gliding position; Inverse dynamics; Passive drag

Mesh:

Year:  2015        PMID: 26087879     DOI: 10.1016/j.jbiomech.2015.03.005

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  3 in total

1.  Individual-Environment Interactions in Swimming: The Smallest Unit for Analysing the Emergence of Coordination Dynamics in Performance?

Authors:  Brice Guignard; Annie Rouard; Didier Chollet; John Hart; Keith Davids; Ludovic Seifert
Journal:  Sports Med       Date:  2017-08       Impact factor: 11.136

2.  Backstroke to Breaststroke Turning Performance in Age-Group Swimmers: Hydrodynamic Characteristics and Pull-Out Strategy.

Authors:  Phornpot Chainok; Leandro Machado; Karla de Jesus; J Arturo Abraldes; Márcio Borgonovo-Santos; Ricardo J Fernandes; João Paulo Vilas-Boas
Journal:  Int J Environ Res Public Health       Date:  2021-02-14       Impact factor: 3.390

3.  Monitoring Master Swimmers' Performance and Active Drag Evolution along a Training Mesocycle.

Authors:  Henrique P Neiva; Ricardo J Fernandes; Ricardo Cardoso; Daniel A Marinho; J Arturo Abraldes
Journal:  Int J Environ Res Public Health       Date:  2021-03-30       Impact factor: 3.390

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.